Victoria’s Secret Sauce – Web Analytics and Customer Experience Optimization

Introduction

Victoria’s Secret is a women’s fashion brand owned by parent company Limited Brands. As of January 2012, Victoria’s Secret has 1,017 stores with over 6 million square feet of selling space inside these stores. Inside a VS store, you will find a dazzling assortment of intimate apparel, beauty products, sleepwear, hosiery and more (About, 2012).

Victoria’s Secret Direct is the business arm that handles the Victoria’s Secret Catalogue and its ecommerce site, VictoriasSecret.com. VS Direct makes it possible for customers to have a great VS customer experience anytime and anywhere they want. The VS Catalogue reaches more than 390 million customers each year. The VS website and catalogue together brought in over $1.5 billion in net sales last year, a 4% sales increase (About, 2012).

Web Analytics Techniques the Company is Employing

Victoria’s Secret uses IBM Coremetrics to collect web analytics data from their website. VS began using Coremetrics in 2002, before the analytics company was bought in 2010 by IBM. Victoria’s Secret specifically uses Marketforce, a complete data capture, storage and decision-support system that gives companies knowledge of customer and visitor activity online. The Coremetrics marketing analytics platform captures and stores all customer and visitor clickstream activity to build LIVE (Lifetime Individual Visitor Experience) Profiles of online customers and visitors over time and across digital channels (Peters, 2002).

Fast forward 10 years, and now IBM owns Coremetrics and has integrated into the IBM Digital Marketing Optimization Suite, which itself is part of the IBM Enterprise Marketing Management Suite. Marketers are provided with a data warehouse on visitor’s digital journeys, across marketing touchpoints and channels, and even offline (IBM, 2012). Real-time KPIs and dashboards, mobile device analytics, powerful attribution capabilities, ad-hoc explorative analysis and reporting, segmentation capabilities, custom reporting are all features of the integrated Coremetrics platform.

How They Are Using Collected Data

The reason for Victoria’s Secret using analytics is to optimize the online customer experience and improve profitability. When they first began using Coremetrics, the goals were to use the knowledge gained to optimize the shopping path design, reduce website abandonment rates and improve retention marketing initiatives (Peters, 2002).

“We are very focused on customer service, with a firm commitment to making the online experience as rewarding for customers as our catalog and in-store experiences. Coremetrics provides extremely detailed analysis of our customers’ online behavior, delivering insights that help us improve the online shopping experience and run our web site more effectively. The combination of a rewarding shopping experience and increased efficiencies in managing our online channel has resulted in opportunities for revenue enhancement,” said Ken Weil, the vice president of new media at Victoria’s Secret (Peters, 2002).

Victoria’s Secret was ahead of its time in being this concerned with their online customer experience optimization. Many Internet retailers today still have not embraced the concept of customer experience optimization like they should be. Failing to realize how important the unique experience that customers have with your brand could be fatal in the competitive business environment today.

According to the Victoria’s Secret privacy policy, cookies and clear gifs are used to better understand website user behavior. Helping to improve the VS site, provide better customer service, personalize user’s online experience, and personalize offers based on user’s unique tastes, interactions and purchase history are all ways that VS uses the data it acquires about customers and website visitors (Privacy, 2012).

Tools, Data Collection Methods, or Metrics that Could Improve Overall Web Analytics Efforts

Since Victoria’s Secret spent about $12 million on the Victoria’s Secret Fashion Show this year that aired on CBS on December 4, VS marketers should collect data and follow metrics that are specifically for the fashion show. According to financial analysts, the show pays for itself as a marketing tactic because of the sales increases that occur during and after the fashion show (Maheshwari, 2012).

According to Ed Razek, Chief Marketing Officer of creative services of Limited Brands, “you see sales results almost immediately. On the night of the show you see substantial increases in our web business from all of the news coverage. The day after the fashion show runs on television, you see substantial increases in our web business” (Amed, 2011).

Sales increases are great, but the VS Fashion Show is about more than just sales increases—it is the cornerstone to the VS integrated marketing communications strategy that drives brand awareness as well as sales across retail, catalogue and online channels. According to a Dartmouth case study, when Leslie Wexner bought Victoria’s Secret, he wanted to make it “stand out as an integrated world-class brand. The same products are launched at the same time, in exactly the same way, with the same quality and positioning” (Durbin, 2002).

Since VS has both sales and brand awareness goals associated with the VS Fashion Show, these goals should be connected to web metrics that can measure them. I would find a way to measure all inbound traffic sent by the fashion show. A specific landing page for people visiting the website because of the show would separate traffic generated from the show from regular traffic. Brand awareness could be measured by quantifying the social media mentions, posts and conversations that have to do with the VS fashion show. Sentiment analysis for specific show-related keywords could show the lift that the VS brand receives because of the show.

Conclusion

Victoria’s Secret is doing many things right, and they are way ahead of many other Internet retailers when it comes to optimizing their customer experience. But there are always improvements that can be done, and I think using web metrics to show how successful the Victoria’s Secret Fashion Show is something VS marketers should definitely do.

References

About Victoria’s Secret. (2012). Limited Brands. Retrieved on 12/10/12 from http://www.limitedbrands.com/our_brands/victorias_secret/about.aspx

Amed, I. (21 November 2011). Addressing Fashion’s Communications Conundrum. The Business of Fashion. Retrieved on 12/10/12 from http://www.businessoffashion.com/2011/11/addressing-fashions-communications-conundrum.html#more-26875

Durbin, T. (2002). Victoria’s Secret. Tuck School of Business at Dartmouth: Center for Digital Strategies. Retrieved on 12/10/12 from http://digitalstrategies.tuck.dartmouth.edu/cds-uploads/case-studies/pdf/6-0014.pdf

IBM Digital Analytics. (November 2012). IBM Software Data Sheet. Retrieved on 12/10/12 from http://public.dhe.ibm.com/common/ssi/ecm/en/zzd03044usen/ZZD03044USEN.PDF

Maheshwari, S. (20 November 2012). The marketing secrets of Victoria’s Secret. Chicago Tribune. Retrieved on 12/10/12 from http://www.chicagotribune.com/business/ct-biz-1120-bf-secret-marketing-20121120,0,5870626.story

Peters, K. (29 July 2002). Victoria’s Secret Selects Coremetrics to Optimize the Online Customer Experience and Improve Profitability. Internet Retailer. Retrieved on 12/10/12 from http://www.internetretailer.com/2002/07/30/victoria-s-secret-selects-coremetrics-to-optimize-the-online-c

Privacy Statement. (26 October 2012). Privacy & Security. Victoria’s Secret. Retrieved on 12/10/12 from http://www.victoriassecret.com/privacy-and-security#technology

Goals, Funnels & Filters in Google Analytics

Introduction

Google Analytics provides many different metrics about your website visitors. Audience demographics, behavior and ecommerce information are just some of the useful metrics available in GA. But what if you need information on a specific event, like a conversion? Or what if you want to drill further down into your data? Or what if you need to have more control over segmenting your visitors?

Well Google Analytics has an answer to these questions, and they are goals, funnels and filters. All three of these help you to better understand your website visitors, and they are discussed further below.

Goals

Defining the goals of a website is one of the best ways to track and measure the effectiveness of your website. Goals should be tied to your business objectives that the website is supposed to accomplish, whether that is selling a product or gathering leads for follow-up sales calls. Goals can be set up in Google Analytics to track exactly what is important to your business. All websites should have at least one goal.

In Google Analytics there are four types of goals that can be created and tracked: 1) a URL destination goal, 2) a Time on Site goal, 3) a Pages/Visit goal, and 4) an Event goal (Goals, 2012).

A URL destination goal triggers a conversion when a visitor views a specified page on your website after completing a specific activity, like filling out a form, downloading a whitepaper or purchasing a product (Goals, 2012). As an example, we will use a company that has a website with the purpose of collecting sales leads. The main goal for this website should be users filling out the sales call request form. This goal can be set up by going to the Goals section in Google Analytics.

Time on site and pages per visit goals are useful for measuring website engagement. If you have content website and your objective is to get users to view as much content as possible, a pages per visit goal would be a good one to track.

There are numerous metrics that are tracked for each goal that is set up. Number of goal competitions, goal value in dollars, goal conversion rate and total abandonment rate are all metrics that are tracked for each goal. The source or medium for each goal completion is also tracked, along with the goal completion percent for each source or medium. This enables businesses and marketers to compare the goal conversion percent for each source and medium that sent traffic that lead to a goal conversion.

Funnels

For each goal, you can define a funnel, which is the path you expect your website visitors to take on their way to completing a goal (Lesson 6, 2012). There is a report called Reverse Goal Path that can also provide useful information about your website’s goal conversions. This report shows you how many users converted from each path. This can help you recognize funnels that you had not previously considered (Goals, 2012).

Multi-channel funnels are another type of funnel that shows how different traffic sources work together to create sales and conversions (About, 2012). I discussed the multi-channel funnels report last week, including how calculating the Return on Investment (ROI) of each channel can help you understand which channels are performing the best.

I also spoke about the importance of useing the multi-channel funnel report to spot trouble spots in your business’s conversion funnel. Spotting the point where potential customers are dropping out of the conversion funnel, and fixing whatever the problem is, can instantly raise your websites conversion rates. For example, if a lot of potential customers are dropping off on the page that asks for shipping information, maybe there is something wrong with that page, or maybe people think you are charging too much for shipping. Do some tests to find out. Make a discounted or free over a certain amount spent shipping campaign to see if that reduces the drop-offs on that page.

Filters

In Google Analytics, filters allow you increased flexibility with your data by letting you define what data is included in your report and how it appears. You can use filters to customize reports so that the most useful data is highlighted. Some popular uses for filters are removing traffic from internal company sources, restricting data for a profile or user, segmenting data and customizing data. The two types of filters are predefined filters and custom filters (Filters, 2012).

There are three types of predefined filters: 1) exclude traffic from domains, 2) exclude traffic from the IP addresses, and 3) include only traffic to the subdirectories (Filters, 2012). As a best practice Google recommends excluding all website traffic from inside your company because including this internal company traffic will not give accurate measures of your target market’s website behavior.

Custom filters offer you greater control of what data appears in your Google Analytics reports. Exclude, include, lowercase/uppercase, search & replace, and advanced are all types of custom filters. The exclude and include filters are the most common filters used, and are often used to segment data by geographical region (Filters, 2012).

By using profiles and filters, you can customize your data views. For example, you can create separate profiles with filters that segment traffic by referring source, geography or user-defined variable. Google recommends always keeping one profile with all your data, so that you always have access to all your data. Here is a visual that shows the example segments created with profiles and filters (Filters, 2012):

Using filters, you can set up a profile that only includes traffic sent by Google AdWords. This will help you to better analyze the website traffic that AdWords is sending your way. Another custom filter that will help businesses make better decisions is segmenting by geographic region. For example, say a company has four sales regions— Northeast, Southeast, Northwest and Southwest, and they need to know website metrics on each of these regions. Using filters is an effective way to segment website visitors so that each segment may be analyzed.

References

About this report. (2012). Multi-Channel Funnels. Google Analytics. Retrieved on 12/3/12 from www.google.com/analytics

Filters in Google Analytics. (2012). Google Analytics IQ Lessons. Google Analytics. Retrieved on 12/3/12 from http://www.google.com/analytics/iq.html

Goals in Google Analytics. (2012). Google Analytics IQ Lessons. Google Analytics. Retrieved on 12/3/12 from http://www.google.com/analytics/iq.html

Lesson 6. (22 October 2012). P.I. Reed School of Journalism. WVU. Retrieved on 12/2/12 from eCampus.